Special Variables

When the Python interpeter reads a source file, it first defines a few special variables. In this case, we care about the __name__ variable.

When Your Module Is the Main Program

If you are running your module (the source file) as the main program, e.g.

python foo.py

the interpreter will assign the hard-coded string "__main__" to the __name__ variable, i.e.

# It's as if the interpreter inserts this at the top
# of your module when run as the main program.
__name__ = "__main__"

When Your Module Is Imported By Another

On the other hand, suppose some other module is the main program and it imports your module. This means there's a statement like this in the main program, or in some other module the main program imports:

# Suppose this is in some other main program.
import foo

In this case, the interpreter will look at the filename of your module, foo.py, strip off the .py, and assign that string to your module's __name__ variable, i.e.

# It's as if the interpreter inserts this at the top
# of your module when it's imported from another module.
__name__ = "foo"

Executing the Module's Code

After the special variables are set up, the interpreter executes all the code in the module, one statement at a time. You may want to open another window on the side with the code sample so you can follow along with this explanation.

Always

It prints the string "before import" (without quotes).

It loads the math module and assigns it to a variable called math. This is equivalent to replacing import math with the following (note that __import__ is a low-level function in Python that takes a string and triggers the actual import):

# Find and load a module given its string name, "math",
# then assign it to a local variable called math.
math = __import__("math")

It prints the string "before functionA".

It executes the def block, creating a function object, then assigning that function object to a variable called functionA.

It prints the string "before functionB".

It executes the second def block, creating another function object, then assigning it to a variable called functionB.

It prints the string "before __name__ guard".

Only When Your Module Is the Main Program

If your module is the main program, then it will see that __name__ was indeed set to "__main__" and it calls the two functions, printing the strings "Function A" and "Function B 10.0".

Only When Your Module Is Imported by Another

(instead) If your module is not the main program but was imported by another one, then __name__ will be "foo", not "__main__", and it'll skip the body of the if statement.

Always

It will print the string "after __name__ guard" in both situations.

Summary

In summary, here's what'd be printed in the two cases:

# What gets printed if foo is the main program
before import
before functionA
before functionB
before __name__ guard
Function A
Function B 10.0
after __name__ guard

# What gets printed if foo is imported as a regular module
before import
before functionA
before functionB
before __name__ guard
after __name__ guard

Why Does It Work This Way?

You might naturally wonder why anybody would want this. Well, sometimes you want to write a .py file that can be both used by other programs and modules as a module and can be run as the main program. Examples:

Your module is a library, but you want to have a script mode where it runs some unit tests or a demo.

Your module is only used as a main program, but it has some unit tests, and the testing framework works by importing .py files like your script and running special test functions. You don't want it to try running the script just because it's importing the module.

Your module is mostly used as a main program, but it also provides a programmer-friendly API for advanced users.

Beyond those examples, it's elegant that running a script in Python is just setting up a few magic variables and importing the script. "Running" the script is a side effect of importing the script's module.

Food for Thought

Question: Can I have multiple __name__ checking blocks? Answer: it's strange to do so, but the language won't stop you.

Suppose the following is in foo2.py. What happens if you say python foo2.py on the command-line? Why?

Out of curiosity: What hapens if I run subprocess.run('foo_bar.py') in a python script? I suppose that foo_bar will be started with __name__ = '__main__' just like when I tipe foo_bar.py in cmd manually. Is that the case? Taking @MrFooz' Answer into account there should not be any problem doing this and having as many "main" modules at a time as I like. Even changing the __name__ value or having several independantly creates instances (or instances that created each other by subprocess) interact with each other should be business as usual for Python. Do I miss something?
– hajefFeb 18 at 16:09

1

@hajef You're correct about how things would work with subprocess.run. That said, a generally better way of sharing code between scripts is to create modules and have the scripts call the shared modules instead of invoking each other as scripts. It's hard to debug subprocess.run calls since most debuggers don't jump across process boundaries, it can add non-trivial system overhead to create and destroy the extra processes, etc.
– Mr FoozFeb 19 at 16:16

1

i have a doubt in foo2.py example in the food for thought section.what does from foo2.py import functionB do? In my view it just imports foo2.py from functionB
– user471651Feb 24 at 13:47

@MrFooz I never intended to do anything like this xD It just came to my mind and I realized that it was strange enought to possibly help ppl. wrapping their minds around this sort of stuff. @user471651 Why should from foo2 import functionB import foo2 from functionB? That's a semantic contortion. from module import method imports the method from the modul.
– hajefFeb 25 at 15:51

When your script is run by passing it as a command to the Python interpreter,

python myscript.py

all of the code that is at indentation level 0 gets executed. Functions and classes that are defined are, well, defined, but none of their code gets run. Unlike other languages, there's no main() function that gets run automatically - the main() function is implicitly all the code at the top level.

In this case, the top-level code is an if block. __name__ is a built-in variable which evaluates to the name of the current module. However, if a module is being run directly (as in myscript.py above), then __name__ instead is set to the string "__main__". Thus, you can test whether your script is being run directly or being imported by something else by testing

if __name__ == "__main__":
...

If your script is being imported into another module, its various function and class definitions will be imported and its top-level code will be executed, but the code in the then-body of the if clause above won't get run as the condition is not met. As a basic example, consider the following two scripts:

# file one.py
def func():
print("func() in one.py")
print("top-level in one.py")
if __name__ == "__main__":
print("one.py is being run directly")
else:
print("one.py is being imported into another module")

# file two.py
import one
print("top-level in two.py")
one.func()
if __name__ == "__main__":
print("two.py is being run directly")
else:
print("two.py is being imported into another module")

Now, if you invoke the interpreter as

python one.py

The output will be

top-level in one.py
one.py is being run directly

If you run two.py instead:

python two.py

You get

top-level in one.py
one.py is being imported into another module
top-level in two.py
func() in one.py
two.py is being run directly

Thus, when module one gets loaded, its __name__ equals "one" instead of "__main__".

As you can see, when a module is imported, Python sets globals()['__name__'] in this module to the module's name. Also, upon import all the code in the module is being run. As the if statement evaluates to False this part is not executed.

$ python b.py
Hello World from __main__!
Hello World again from __main__!

As you can see, when a file is executed, Python sets globals()['__name__'] in this file to "__main__". This time, the if statement evaluates to True and is being run.

What does the if __name__ == "__main__": do?

The global variable, __name__, in the module that is the entry point to your program, is '__main__'. Otherwise, it's the name you import the module by.

So, code under the if block will only run if the module is the entry point to your program.

It allows the code in the module to be importable by other modules, without executing the code block beneath on import.

Why do we need this?

Developing and Testing Your Code

Say you're writing a Python script designed to be used as a module:

def do_important():
"""This function does something very important"""

You could test the module by adding this call of the function to the bottom:

do_important()

and running it (on a command prompt) with something like:

~$ python important.py

The Problem

However, if you want to import the module to another script:

import important

On import, the do_important function would be called, so you'd probably comment out your function call, do_important(), at the bottom.

# do_important() # I must remember to uncomment to execute this!

And then you'll have to remember whether or not you've commented out your test function call. And this extra complexity would mean you're likely to forget, making your development process more troublesome.

A Better Way

The __name__ variable points to the namespace wherever the Python interpreter happens to be at the moment.

Inside an imported module, it's the name of that module.

But inside the primary module (or an interactive Python session, i.e. the interpreter's Read, Eval, Print Loop, or REPL) you are running everything from its "__main__".

So if you check before executing:

if __name__ == "__main__":
do_important()

With the above, your code will only execute when you're running it as the primary module (or intentionally call it from another script).

An Even Better Way

There's a Pythonic way to improve on this, though.

What if we want to run this business process from outside the module?

If we put the code we want to exercise as we develop and test in a function like this and then do our check for '__main__' immediately after:

We now have a final function for the end of our module that will run if we run the module as the primary module.

It will allow the module and its functions and classes to be imported into other scripts without running the main function, and will also allow the module (and its functions and classes) to be called when running from a different '__main__' module, i.e.

This module represents the (otherwise anonymous) scope in which the
interpreter’s main program executes — commands read either from
standard input, from a script file, or from an interactive prompt. It
is this environment in which the idiomatic “conditional script” stanza
causes a script to run:

There are lots of different takes here on the mechanics of the code in question, the "How", but for me none of it made sense until I understood the "Why". This should be especially helpful for new programmers.

When you execute xy.py, you import ab. The import statement runs the module immediately on import, so ab's operations get executed before the remainder of xy's. Once finished with ab, it continues with xy.

The interpreter keeps track of which scripts are running with __name__. When you run a script - no matter what you've named it - the interpreter calls it "__main__", making it the master or 'home' script that gets returned to after running an external script.

Any other script that's called from this "__main__" script is assigned its filename as its __name__ (e.g., __name__ == "ab.py"). Hence, the line if __name__ == "__main__": is the interpreter's test to determine if it's interpreting/parsing the 'home' script that was initially executed, or if it's temporarily peeking into another (external) script. This gives the programmer flexibility to have the script behave differently if it's executed directly vs. called externally.

Let's step through the above code to understand what's happening, focusing first on the unindented lines and the order they appear in the scripts. Remember that function - or def - blocks don't do anything by themselves until they're called. What the interpreter might say if mumbled to itself:

Open xy.py as the 'home' file; call it "__main__" in the __name__ variable.

What's this? An if statement. Well, the condition has been met (the variable __name__ has been set to "__main__"), so I'll enter the main() function and print 'main function: this is where the action is'.

The bottom two lines mean: "If this is the "__main__" or 'home' script, execute the function called main()". That's why you'll see a def main(): block up top, which contains the main flow of the script's functionality.

Why implement this?

Remember what I said earlier about import statements? When you import a module it doesn't just 'recognize' it and wait for further instructions - it actually runs all the executable operations contained within the script. So, putting the meat of your script into the main() function effectively quarantines it, putting it in isolation so that it won't immediately run when imported by another script.

Again, there will be exceptions, but common practice is that main() doesn't usually get called externally. So you may be wondering one more thing: if we're not calling main(), why are we calling the script at all? It's because many people structure their scripts with standalone functions that are built to be run independent of the rest of the code in the file. They're then later called somewhere else in the body of the script. Which brings me to this:

But the code works without it

Yes, that's right. These separate functions can be called from an in-line script that's not contained inside a main() function. If you're accustomed (as I am, in my early learning stages of programming) to building in-line scripts that do exactly what you need, and you'll try to figure it out again if you ever need that operation again ... well, you're not used to this kind of internal structure to your code, because it's more complicated to build and it's not as intuitive to read.

But that's a script that probably can't have its functions called externally, because if it did it would immediately start calculating and assigning variables. And chances are if you're trying to re-use a function, your new script is related closely enough to the old one that there will be conflicting variables.

In splitting out independent functions, you gain the ability to re-use your previous work by calling them into another script. For example, "example.py" might import "xy.py" and call x(), making use of the 'x' function from "xy.py". (Maybe it's capitalizing the third word of a given text string; creating a NumPy array from a list of numbers and squaring them; or detrending a 3D surface. The possibilities are limitless.)

(As an aside, this question contains an answer by @kindall that finally helped me to understand - the why, not the how. Unfortunately it's been marked as a duplicate of this one, which I think is a mistake.)

When there are certain statements in our module (M.py) we want to be executed when it'll be running as main (not imported), we can place those statements (test-cases, print statements) under this if block.

As by default (when module running as main, not imported) the __name__ variable is set to "__main__", and when it'll be imported the __name__ variable will get a different value, most probably the name of the module ('M').
This is helpful in running different variants of a modules together, and separating their specific input & output statements and also if there are any test-cases.

In short, use this 'if __name__ == "main" ' block to prevent (certain) code from being run when the module is imported.

But just block A (and not B) is run when we are running another module, "y.py" for example, in which x.y is imported and the code is run from there (like when a function in "x.py" is called from y.py).

As you can see, __name__ tells us which code is the 'main' module.
This is great, because you can just write code and not have to worry about structural issues like in C/C++, where, if a file does not implement a 'main' function then it cannot be compiled as an executable and if it does, it cannot then be used as a library.

Say you write a Python script that does something great and you implement a boatload of functions that are useful for other purposes. If I want to use them I can just import your script and use them without executing your program (given that your code only executes within the if __name__ == "__main__": context). Whereas in C/C++ you would have to portion out those pieces into a separate module that then includes the file. Picture the situation below;

The arrows are import links. For three modules each trying to include the previous modules code there are six files (nine, counting the implementation files) and five links. This makes it difficult to include other code into a C project unless it is compiled specifically as a library. Now picture it for Python:

You write a module, and if someone wants to use your code they just import it and the __name__ variable can help to separate the executable portion of the program from the library part.

When you run Python interactively the local __name__ variable is assigned a value of __main__. Likewise, when you execute a Python module from the command line, rather than importing it into another module, its __name__ attribute is assigned a value of __main__, rather than the actual name of the module. In this way, modules can look at their own __name__ value to determine for themselves how they are being used, whether as support for another program or as the main application executed from the command line. Thus, the following idiom is quite common in Python modules:

if __name__ == '__main__':
# Do something appropriate here, like calling a
# main() function defined elsewhere in this module.
main()
else:
# Do nothing. This module has been imported by another
# module that wants to make use of the functions,
# classes and other useful bits it has defined.

It checks if the __name__ attribute of the Python script is "__main__". In other words, if the program itself is executed, the attribute will be __main__, so the program will be executed (in this case the main() function).

However, if your Python script is used by a module, any code outside of the if statement will be executed, so if \__name__ == "\__main__" is used just to check if the program is used as a module or not, and therefore decides whether to run the code.

Before explaining anything about if __name__ == '__main__' it is important to understand what __name__ is and what it does.

What is __name__?

__name__ is a DunderAlias - can be thought of as a global variable (accessible from modules) and works in a similar way to global.

It is a string (global as mentioned above) as indicated by type(__name__) (yielding <class 'str'>), and is an inbuilt standard for both Python 3 and Python 2 versions.

Where:

It can not only be used in scripts but can also be found in both the interpreter and modules/packages.

Interpreter:

>>> print(__name__)
__main__
>>>

Script:

test_file.py:

print(__name__)

Resulting in __main__

Module or package:

somefile.py:

def somefunction():
print(__name__)

test_file.py:

import somefile
somefile.somefunction()

Resulting in somefile

Notice that when used in a package or module, __name__ takes the name of the file. The path of the actual module or package path is not given, but has its own DunderAlias __file__, that allows for this.

You should see that, where __name__, where it is the main file (or program) will always return __main__, and if it is a module/package, or anything that is running off some other Python script, will return the name of the file where it has originated from.

Practice:

Being a variable means that it's value can be overwritten ("can" does not mean "should"), overwriting the value of __name__ will result in a lack of readability. So do not do it, for any reason. If you need a variable define a new variable.

It is always assumed that the value of __name__ to be __main__ or the name of the file. Once again changing this default value will cause more confusion that it will do good, causing problems further down the line.

It is considered good practice in general to include the if __name__ == '__main__' in scripts.

Now to answer if __name__ == '__main__':

Now we know the behaviour of __name__ things become clearer:

An if is a flow control statement that contains the block of code will execute if the value given is true. We have seen that __name__ can take either
__main__ or the file name it has been imported from.

This means that if __name__ is equal to __main__ then the file must be the main file and must actually be running (or it is the interpreter), not a module or package imported into the script.

If indeed __name__ does take the value of __main__ then whatever is in that block of code will execute.

This tells us that if the file running is the main file (or you are running from the interpreter directly) then that condition must execute. If it is a package then it should not, and the value will not be __main__.

Modules:

__name__ can also be used in modules to define the name of a module

Variants:

It is also possible to do other, less common but useful things with __name__, some I will show here:

Executing only if the file is a module or package:

if __name__ != '__main__':
# Do some useful things

Running one condition if the file is the main one and another if it is not:

__name__: Every module in Python has a special attribute called __name__.
It is a built-in variable that returns the name of the module.

__main__: Like other programming languages, Python too has an execution entry point, i.e., main. '__main__'is the name of the scope in which top-level code executes. Basically you have two ways of using a Python module: Run it directly as a script, or import it. When a module is run as a script, its __name__ is set to __main__.

Thus, the value of the __name__ attribute is set to __main__ when the module is run as the main program. Otherwise the value of __name__ is set to contain the name of the module.

It is a special for when a Python file is called from the command line. This is typically used to call a "main()" function or execute other appropriate startup code, like commandline arguments handling for instance.

I am not saying you should use this in production code, but it serves to illustrate that there is nothing "magical" about if __name__ == '__main__'. It is a good convention for invoking a main function in Python files.

I would consider this bad form as you're 1) relying on side effects and 2) abusing and. and is used for checking if two boolean statements are both true. Since you're not interested in the result of the and, an if statement more clearly communicates your intentions.
– jpmc26Dec 26 '13 at 18:07

8

Leaving aside the question of whether exploiting the short-circuit behaviour of boolean operators as a flow control mechanism is bad style or not, the bigger problem is that this doesn't answer the question at all.
– Mark AmeryJul 10 '15 at 15:33

There are a number of variables that the system (Python interpreter) provides for source files (modules). You can get their values anytime you want, so, let us focus on the __name__ variable/attribute:

When Python loads a source code file, it executes all of the code found in it. (Note that it doesn't call all of the methods and functions defined in the file, but it does define them.)

Before the interpreter executes the source code file though, it defines a few special variables for that file; __name__ is one of those special variables that Python automatically defines for each source code file.

If Python is loading this source code file as the main program (i.e. the file you run), then it sets the special __name__ variable for this file to have a value "__main__".

If this is being imported from another module, __name__ will be set to that module's name.

will be executed only when you run the module directly; the code block will not execute if another module is calling/importing it because the value of __name__ will not equal to "main" in that particular instance.

is primarily to avoid the import lock problems that would arise from having code directly imported. You want main() to run if your file was directly invoked (that's the __name__ == "__main__" case), but if your code was imported then the importer has to enter your code from the true main module to avoid import lock problems.

A side-effect is that you automatically sign on to a methodology that supports multiple entry points. You can run your program using main() as the entry point, but you don't have to. While setup.py expects main(), other tools use alternate entry points. For example, to run your file as a gunicorn process, you define an app() function instead of a main(). Just as with setup.py, gunicorn imports your code so you don't want it do do anything while it's being imported (because of the import lock issue).

I've been reading so much throughout the answers on this page. I would say, if you know the thing, for sure you will understand those answers, otherwise, you are still confused.

To be short, you need to know several points:

import a action actually runs all that can be ran in "a"

Because of point 1, you may not want everything to be run in "a" when importing it

To solve the problem in point 2, python allows you to put a condition check

__name__ is an implicit variable in all .py modules; when a.py is imported, the value of __name__ of a.py module is set to its file name "a"; when a.py is run directly using "python a.py", which means a.py is the entry point, then the value of __name__ of a.py module is set to a string __main__

Based on the mechanism how python sets the variable __name__ for each module, do you know how to achieve point 3? The answer is fairly easy, right? Put a if condition: if __name__ == "__main__": ...; you can even put if __name__ == "a" depending on your functional need

The important thing that python is special at is point 4! The rest is just basic logic.

The above statement is true and prints "direct method". Suppose if they imported this class in another class it doesn't print "direct method" because, while importing, it will set __name__ equal to "first model name".

All the answers have pretty much explained the functionality. But I will provide one example of its usage which might help clearing out the concept further.

Assume that you have two Python files, a.py and b.py. Now, a.py imports b.py. We run the a.py file, where the "import b.py" code is executed first. Before the rest of the a.py code runs, the code in the file b.py must run completely.

In the b.py code there is some code that is exclusive to that file b.py and we don't want any other file (other than b.py file), that has imported the b.py file, to run it.

So that is what this line of code checks. If it is the main file (i.e., b.py) running the code, which in this case it is not (a.py is the main file running), then only the code gets executed.

This answer makes the assumption that the OP (or any user with a similar question) is both familiar with Cand knows what an entry point is.
– arredondFeb 22 at 12:44

This answer also assumes that no code (other than definitions without side effects) take place before the if __name__ == "__main__" block. Technically the top of the script executed is the entry point of the program.
– Charlie HardingApr 9 at 21:35